Increasingly, industry is turning to statistical reliability analysis for equipment and products. Such statistical reliability analysis is useful in planning and budgeting for maintenance, predicting costs associated with product warranties, and making decisions about maintenance of a particular device. In addition, some manufacturers have turned to statistical reliability analysis to make decisions about upgrades to upcoming product releases.
Traditional statistical reliability analysis and, in particular, Weibull analysis relies on failure data for a population of devices. If a complete data set is available (i.e., failure ages are known for each device within the population), statistical reliability analysis, such as Weibull analysis, can provide predictions, such as mean-time-to-failure for a particular device, percentages of devices that will fail at a particular time or before a particular age, a statistical distribution of failure ages, and other statistical measures of device failures. The age of a particular device may be measured in operating times, such as time in service, or other cumulative performance measures, such as mileage or cycles or the number of revolutions.
However, a typical population includes devices that have yet to fail, termed “suspensions.” In Weibull analysis, such populations are often denoted as “right censored populations.” While analysis techniques for suspension populations have been developed, these analysis techniques typically rely on snapshots of population data including both the suspension data and failure data.
Often though, detailed information of the status of actual devices in service is incomplete or nonexistent. If the data does exist, it may be difficult to compile for use as suspension data, or it may change so often that taking a snapshot for each reliability analysis would be impractical. Furthermore, the data may exist in the form of ‘x’ units within a certain age range, ‘y’ units within another age range, etc. Other possible reasons that the data would be difficult to compile include large populations serviced in different locations, the maintenance records being in paper format, or the part information has to be extracted from long text narratives, etc. As such, an improved system and method would be desirable for analyzing the reliability of populations of devices.